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Generative Ai Finance Jobs in Indiana (NOW HIRING)

$84K - $111K/yr

As generative AI tools become deeply embedded in our engineering and corporate workflows, you will ... Lead a FinOps Champion Network across engineering, finance, and product teams, establishing shared ...

Familiarity with Generative AI concepts , AI platforms, and enterprise adoption considerations (strong asset). * Strong business acumen with deep understanding of: * Financial systems * Corporate and ...

Familiarity with generative AI models (ChatGPT, Gemini, etc.) and prompt development. * Must be based in New York City. Preferred Requirements: * Background in financial services, fintech, or digital ...

Showing results 21-40

Generative Ai Finance information

What is generative AI finance?

Generative AI Finance refers to the use of advanced artificial intelligence models, such as generative adversarial networks (GANs) and large language models, in financial services and operations. These technologies are used for tasks like automating financial reporting, generating investment strategies, detecting fraud, and forecasting market trends. Generative AI can analyze vast amounts of financial data, create realistic simulations, and generate insights that can help financial institutions make better decisions. As the field grows, it is transforming how banks, investment firms, and other financial organizations approach data analysis, risk management, and customer service.

How does a generative AI finance professional typically collaborate with cross-functional teams within an organization?

Generative AI Finance professionals frequently work alongside data scientists, software engineers, and financial analysts to develop and implement AI-driven models for forecasting, risk assessment, and process automation. Collaboration is key, as finance experts provide domain knowledge while technical teams handle the model development and deployment. Regular meetings, shared project management tools, and clear communication channels help ensure alignment on project goals and timelines. These professionals also often present findings and recommendations to stakeholders, bridging the gap between technical solutions and business needs.

What are the key skills and qualifications needed to thrive as a generative AI finance professional, and why are they important?

To thrive as a Generative AI Finance professional, you need a strong background in finance, data analysis, and machine learning, often supported by degrees in finance, mathematics, computer science, or related fields. Familiarity with AI frameworks (such as TensorFlow or PyTorch), programming languages (like Python), and financial modeling tools is typically required, along with relevant certifications in finance or data science. Strong problem-solving, communication, and adaptability skills help professionals bridge the gap between technical teams and business stakeholders. These skills and qualities are crucial for designing innovative AI-driven financial solutions that are accurate, reliable, and aligned with business objectives.

What is the difference between Generative Ai Finance vs Data Analyst?

AspectGenerative Ai FinanceData Analyst
Required CredentialsDegree in Finance, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentFinance firms, tech companies, AI startups; focus on AI-driven financial solutionsCorporate, consulting, or financial institutions; focus on data interpretation and reporting
Employer & Industry UsageFinancial institutions integrating AI for predictive modeling and automationOrganizations analyzing data to inform business decisions and strategies

Generative Ai Finance involves developing AI models to generate financial insights, automate tasks, and create synthetic data, often requiring expertise in AI and finance. Data Analysts focus on interpreting existing data to support decision-making. While both roles work with data, Generative Ai Finance emphasizes AI model creation, whereas Data Analysts focus on data interpretation and reporting.

Is generative AI used in finance?

Generative AI is increasingly used in finance for tasks such as algorithmic trading, risk modeling, and fraud detection. Finance professionals, including those in generative AI roles, utilize machine learning tools and data analysis skills to develop models that improve decision-making and automate processes.

What are popular job titles related to Generative Ai Finance jobs in Indiana?

For Generative Ai Finance jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Generative Ai Finance jobs in Indiana look for?

The top searched job categories for Generative Ai Finance jobs in Indiana are:

What cities in Indiana are hiring for Generative Ai Finance jobs?

Cities in Indiana with the most Generative Ai Finance job openings:

Artificial Intelligence (AI) Data Governance Officer

Northwest

Fishers, IN

Full-time

Posted 14 days ago


Job description

IN0534 Fishers, OH0523 Independence Bus Office, OH0713 NW Bancshares HQ, PA0258 Bellevue, PA0736 Administration Center

Job Description

The AI Governance Officer is a senior-level contributor responsible for administering the Bank's enterprise AI governance framework and supporting the oversight of artificial intelligence use cases throughout their lifecycle. The role exercises sound judgment in assessing AI-related risks, facilitating risk-based governance decisions, coordinating cross-functional review processes, and ensuring compliance with internal standards and regulatory expectations. The position plays a critical role in enabling responsible innovation while maintaining transparency, accountability, and effective oversight of AI capabilities deployed across the institution.
Essential Functions
Leads administration of the Bank's enterprise AI risk governance framework and supporting procedures. Coordinates activities across all business lines and corporate functions.
Coordinate intake, assessment, and governance activities for proposed AI use cases. Determine and document the classification of solutions as models, agents, tools, job aids, or other categories defined by policy.
Serve coordinator for the AI Working Group, including preparation of agendas, meeting materials, decision logs, and action item tracking.
Maintain the enterprise inventory of AI use cases and associated governance records.
Assess proposed AI implementations to determine applicable governance requirements and control expectations.
Develop management reporting and dashboards related to AI inventory, approvals, issues, and emerging risks. Monitor compliance with AI governance standards and escalate material issues to executive leadership.
Promote awareness and understanding of AI governance requirements throughout the institution.
Develops and maintains enterprise policies, standards, and procedures governing AI risk.
Serve as a senior member of the Model Risk team, exercising sound judgment in evaluating model risk and making decisions on model approvals and issue closures as a delegate of the Chief Model Risk Officer.
Participate in the research and evaluation of emerging modeling techniques, including AI/ML, and assess their applicability and risk implications within the institution.
Contribute to the development and enhancement of the model risk management framework, including validation methodologies, documentation standards, and governance practices.
Review academic and industry research, summarize key insights, and propose practical applications to improve model risk oversight and innovation.
Ensure compliance with Northwest's policies and procedures, as well as applicable federal and state regulations including SR26-2, interagency AI/ML guidance, and the U.S. Treasury Financial Services AI Risk Management Framework.
Interprets evolving regulatory expectations relating to artificial intelligence and translates them into practical governance requirements.
Serves as the primary coordinator for regulatory examinations, audits, and independent reviews of AI governance.
Additional Essential Functions
Ensure compliance with Northwest's policies and procedures, and Federal/State regulations
Navigate Microsoft Office Software, computer applications, and software specific to the department in order to maximize technology tools and gain efficiency
Work as part of a team
Work with on-site equipment

What You Bring to the Team

Participate in enterprise initiatives involving emerging technologies and advanced analytics.
Own the design, implementation, and enhancement of governance workflows within Archer or similar systems.
Recommend customer service enhancements
QUALIFICATIONS
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Education
Bachelor's Degree Undergraduate degree in risk management, business, economics, statistics, mathematics, information systems, computer science, law, or related discipline.
Master's Degree Master's degree in risk management, business, economics, statistics, mathematics, information systems, computer science, law, or related discipline.
Work Experience
8 - 12 years Experience in a financial institution or consulting environment, with demonstrated exposure to AI governanceAnd
3 - 5 years Experience evaluating or governing AI/ML use cases across the lifecycle, including:
pre-implementation assessment
control design
post-deployment monitoring
Experience with generative AI, machine learning, or decision-support systems, including understanding of associated risks (e.g., bias, explainability, data dependency, automation risk)
Experience supporting or interacting with internal audit, regulators, or independent model review functions
Experience supporting or interacting with internal audit, regulators, or independent model review functions
Additional Knowledge, Skills and Abilities
Ability to apply risk-based judgment in ambiguous situations, particularly in evaluating AI use cases where regulatory expectations and governance standards are evolving
Ability to analyze complex AI/ML concepts and communicate risks, limitations, and trade-offs clearly to both technical and non-technical stakeholders
Ability to challenge and influence business and technology stakeholders to ensure appropriate risk identification, control design, and governance outcomes
Ability to identify patterns, emerging risks, and systemic issues across multiple AI use cases rather than evaluating them in isolation.
Ability to make sound governance decisions in gray areas, including classification (model vs agent vs tool), control requirements, and escalation thresholds
Ability to coordinate cross-functional governance processes and drive clear outcomes across Risk, Technology, Compliance, Legal, and Business teams
Ability to develop and interpret risk metrics, monitoring outputs, and performance indicators for AI systems
Licenses and Certifications
Certified Information Systems Auditor (CISA)
Certified in Risk and Information Systems Control (CRISC)
Financial Risk Manager (FRM)
Certified Third-Party Risk Professional (CTPRP)
Relevant AI governance certifications

Northwest is an equal opportunity employer. We are committed to creating an inclusive environment for all employees.